Coronary CT angiography (CCTA) scans are widely used for diagnosis of
coronary artery diseases. An accurate and automatic vessel labeling algorithm
for CCTA analysis can significantly improve the diagnostic efficiency and
reduce the clinicians'manual efforts. In this paper, we propose a simple vessel
labeling method based on the Point Transformer, which only needs the coronary
artery segmentation. Specifically, firstly, the coronary segmentation is
transformed to point cloud. Then, these points are fed into the hierarchical
transformer blocks to obtain the multi-level features, including local and
global features. Finally, the network output the semantic classification points
and map them to centerline labeling. This method is only based on the structure
of coronary segmentation and need not other features, so it is easy to
generalize to other vessel labeling tasks, e.g., head and neck vessel labeling.
To evaluate the performance of our proposed method, CCTA scans of 53 subjects
are collected in our experiment. The experimental results demonstrate the
efficacy of this approach.

该论文提供了一种基于 Point Transformer 的简单的血管标记方法，只需要冠状动脉分割，能够提高诊断效率和减少临床医生的人工劳动，在 53 位患者的实验中取得了良好的效果。